3 citations · 3 across the 10 of their papers we have counts for
8 papers · 1 filter
Quantifying the Impact of Upright Patient Positioning on Cardiac Substructures Using Deep Learning
Nicholas Summerfield, Yuhao Yan, Chase Ruff +4
Upright patient positioners with diagnostic-quality vertical CT at treatment isocenter may improve image-guided radiation therapy (RT). However, cardiac substructure (CS) geometry…
Cardiac segmentation for ventricular tachycardia radioablation and radiotherapy patients with cardiac implants
Nicholas Summerfield, Dustin Jacqmin, Chase Ruff +8
Deep-learning (DL) segmentation enables cardiac substructure (CS) delineation for advanced cardiac-sparing radiation therapy (RT). Patients presenting for RT may have implantable d…
Bridging cone-beam CT and MRI to stopping power ratio maps: a modality-agnostic Brownian bridge approach to support robust adaptive proton therapy
Yuhao Yan, Qisheng He, Minglei Kang +4
Purpose: Adaptive proton therapy (APT) relies on routine offline CT simulations for updated anatomy. We present a modality-agnostic regularized Brownian bridge (rBBrg) framework to…
Characterizing the Reliability of a Novel Upright CT for Proton Therapy
Yuhao Yan, Jordan Slagowski, Jessica Miller +4
Purpose: To evaluate reliability of upright CT for proton dose calculation and feasibility of a simplified phantom configuration for accelerated routine QA. Methods: A calibration…
Technical assessment of a novel vertical CT system for upright radiotherapy simulation and treatment planning
Jordan M. Slagowski, Yuhao Yan, Jessica R. Miller +4
Purpose: To characterize image quality, imaging dose, and dose calculation accuracy for an upright CT scanner with a six-degree-of-freedom patient positioning system. Methods: Imag…
Modality-AGnostic Image Cascade (MAGIC) for Multi-Modality Cardiac Substructure Segmentation
Nicholas Summerfield, Qisheng He, Alex Kuo +9
Cardiac substructure delineation is emerging in treatment planning to minimize the risk of radiation-induced heart disease. Deep learning offers efficient methods to reduce contour…
Deducing Cardiorespiratory Motion of Cardiac Substructures Using a Novel 5D-MRI Workflow for Radiotherapy
Chase Ruff, Tarun Naren, Oliver Wieben +5
Objective: Cardiotoxicity is a devastating complication of thoracic radiotherapy. Current radiotherapy imaging protocols are insufficient to decouple and quantify cardiac motion, l…
Evaluation of a Novel Quantitative Multiparametric MR Sequence for Radiation Therapy Treatment Response Assessment
Yuhao Yan, R. Adam Bayliss, Adam R. Burr +5
Purpose: To evaluate a Deep-Learning-enhanced MUlti-PArametric MR sequence (DL-MUPA) for treatment response assessment for brain metastases patients undergoing stereotactic radiosu…